A survey that frames data selection, memory optimization, and compute budgeting as coupled bottlenecks in LLM training rather than isolated techniques.
Hybrid and unitary fine-tuning of large language models: Methods and benchmarking under resource constraints,
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Unifying Data, Memory, and Compute Efficiency in LLM training: A Survey
A survey that frames data selection, memory optimization, and compute budgeting as coupled bottlenecks in LLM training rather than isolated techniques.